Menopause

Early prediction of response to ADT plus ARPIs in mHSPC using interpretable machine learning on PSMA PET/CT: a real-world study.

BACKGROUND: Reliable tools for early prediction of treatment response to androgen deprivation therapy (ADT) plus novel androgen receptor pathway inhibitors (ARPIs) in metastatic hormone-sensitive prostate cancer (mHSPC) remain lacking. This study aimed to develop and validate an interpretable machine learning model integrating [⁶⁸Ga]Ga-PSMA PET/CT-derived imaging features to predict response befor...

Identification of common genetic features and pathways for osteoporosis with frozen shoulder by integrated bioinformatics analysis and machine learning.

Frozen shoulder (FS) and osteoporosis (OP) are common age-related degenerative diseases, occurring more frequently in females, which suggests potential molecular links between them. This study aimed to identify shared genetic features and pathways of OP and FS using bioinformatics and machine learning approaches. Gene expression data for OP and FS were obtained from the Gene Expression Omnibus dat...

C-peptide Index under Non-fasting Conditions Can Predict the Likelihood of Future Insulin Therapy in Outpatients with Type 2 Diabetes Mellitus Not Receiving Insulin at Baseline.

Objective This study aimed to develop a clinical model in which the C-peptide index (CPI) under non-fasting conditions can predict future insulin ther...

Deep data consistency: A fast and robust diffusion model-based solver for inverse problems.

Diffusion models have become a successful approach for solving various image inverse problems by providing a powerful diffusion prior. Many studies ha...

Machine learning identifies traumatic experiences as being associated with auditory verbal hallucinations in both a non-clinical population and individuals diagnosed with psychosis.

BACKGROUND: Auditory verbal hallucinations (AVHs) are a core symptom of psychosis but their prevalence in the general population ranges from 5-28 %. M...

Rapid MR examination with deep learning reconstruction improves diagnosis of complicated acute appendicitis.

OBJECTIVE: To evaluate the performance of a non-contrast rapid magnetic resonance imaging (MRI) protocol with deep learning reconstruction (DLR) for i...

BRAIN-MAGNET: A functional genomics atlas for interpretation of non-coding variants.

Genome-wide assessment of genetic variation is becoming routine in genetics, yet functional interpretation of non-coding single nucleotide variants in...

Development and validation of a multiphase computed tomography-based radiomics classifier for differentiating retroperitoneal non-fatty dedifferentiated liposarcoma from leiomyosarcoma.

OBJECTIVE: We aimed to develop and internally validate a radiomics classification model based on multiphase computed tomography (CT) scans for preoper...

Combination of artificial intelligence and chest computed tomography to assess bone mineral density.

OBJECTIVES: To evaluate the diagnostic accuracy of artificial intelligence-assisted opportunistic chest CT for osteoporosis/osteopenia screening in a ...

Advancing osteoporosis opportunistic screening: multicenter validation of a deep learning algorithm using abdominal CT scans.

OBJECTIVES: To develop and do multicenter validation on an algorithm that screens for osteoporosis from abdominal CTs. METHODS: This is a diagnostic a...

Advanced artificial intelligence combined with SERS platforms for diagnosis and therapeutic effects of cancer in clinical applications.

Surface-Enhanced Raman Spectroscopy (SERS) has become a valuable way to detect small amounts of molecules due to its high sensitivity. Nonetheless, ap...

Deep machine learning methods for Parkinson's disease diagnosis: a new direction in decision-making systems.

Parkinson's disease (PD) is a progressive neurodegenerative disorder primarily characterized by the gradual loss of dopamine-producing neurons in the ...

Multidimensional quantification of pain responses using novel rat pain scale reveals the absence of opioid induced hyperalgesia following chronic contingent and non-contingent morphine exposure in rats.

Opioids are often prescribed to treat chronic and post-operative pain, but there is data to suggest that opioid exposure can lead to hyperalgesia or a...

In silico prediction of endocrine activity.

Endocrine-disrupting chemicals (EDCs) pose health risks; yet, conventional in vitro and in vivo testing remains slow, costly, and animal-intensive. En...

Biased minds, sensitive hearts: Divergent neural signatures of interpersonal sensitivity in atypical and non-atypical depression.

BACKGROUND: Atypical depression (AD) is a distinct subtype of depression, with interpersonal sensitivity as one of its core characteristics. However, ...

Artificial intelligence-driven precision treatment of reproductive medicine-related diseases: the optimal protocol choice for IVF-ET.

INTRODUCTION: Optimal ovarian stimulation (OS) selection is critical for IVF success, but expert-based decisions often lack consistency in outcomes, c...

Real-world diagnostic performance of knee MRI protocols accelerated using simultaneous multi-slice acquisition and deep learning reconstruction.

OBJECTIVE: To assess whether accelerated knee MRI protocols using simultaneous multi-slice (SMS) and deep learning reconstruction (DLR) are non-inferi...

DiffMixer: A prediction model based on mixing different frequency features.

Time series forecasting is widely applied in fields such as energy and network security. Various prediction models based on Transformer and MLP archit...

From objective grouping to fuzzy reference intervals: A standardized machine learning approach for thyroid function tests.

BACKGROUND: Accurate interpretation of thyroid function tests (TFTs) requires reliable reference intervals (RIs). Indirect methods based on retrospect...

Use of neural networks to predict a potential osteoporotic metabolic condition based on the panoramic mandibular index.

OBJECTIVE: This study investigates the use of neural networks to predict potential osteoporotic metabolic conditions using the Panoramic Mandibular In...